So I have this new programming paradigm.......

Joseph Redmon

2016-09-25 481b57a96a9ef29b112caec1bb3e17ffb043ceae

 src/crnn_layer.c

@@ -48,23 +48,31 @@

    l.input_layer = malloc(sizeof(layer));
    fprintf(stderr, "\t\t");
    *(l.input_layer) = make_convolutional_layer(batch*steps, h, w, c, hidden_filters, 3, 1, 1,  activation, batch_normalize, 0);
    *(l.input_layer) = make_convolutional_layer(batch*steps, h, w, c, hidden_filters, 3, 1, 1,  activation, batch_normalize, 0, 0);
    l.input_layer->batch = batch;

    l.self_layer = malloc(sizeof(layer));
    fprintf(stderr, "\t\t");
    *(l.self_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, hidden_filters, 3, 1, 1,  activation, batch_normalize, 0);
    *(l.self_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, hidden_filters, 3, 1, 1,  activation, batch_normalize, 0, 0);
    l.self_layer->batch = batch;

    l.output_layer = malloc(sizeof(layer));
    fprintf(stderr, "\t\t");
    *(l.output_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, output_filters, 3, 1, 1,  activation, batch_normalize, 0);
    *(l.output_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, output_filters, 3, 1, 1,  activation, batch_normalize, 0, 0);
    l.output_layer->batch = batch;

    l.output = l.output_layer->output;
    l.delta = l.output_layer->delta;

    l.forward = forward_crnn_layer;
    l.backward = backward_crnn_layer;
    l.update = update_crnn_layer;

#ifdef GPU
    l.forward_gpu = forward_crnn_layer_gpu;
    l.backward_gpu = backward_crnn_layer_gpu;
    l.update_gpu = update_crnn_layer_gpu;

    l.state_gpu = cuda_make_array(l.state, l.hidden*batch*(steps+1));
    l.output_gpu = l.output_layer->output_gpu;
    l.delta_gpu = l.output_layer->delta_gpu;